Yogyakarta, May 21, 2025 – Students of the Faculty of Pharmacy, Universitas Gadjah Mada (UGM), together with students of the Faculty of Engineering succeeded in winning the Joint 2nd Student Prize in the scientific poster competition at the 2025 Annual Meeting of the British Nuclear Medicine Society (BNMS), with their innovative work on the application of artificial intelligence (AI) in cancer therapy.
The interdisciplinary team comprised Anggraini Ihza Rizkita (Faculty of Pharmacy), Ivandi Cahya Pratama, and Rayhan Adi Wicaksono (Faculty of Engineering), who presented a poster titled “Enhancing Correction Accuracy in Bremsstrahlung Dosimetry for 90Y-Ibritumomab Tiuxetan Therapy Using Machine Learning-Based Algorithms.” Displayed during the Poster Session P121, their work attracted strong attention from the jury due to its multidisciplinary approach and the integration of cutting-edge AI technology.
The project, developed by the UGM team, addresses the challenge of achieving accurate dose calculations in bremsstrahlung imaging, a technique used in 90Y-Ibritumomab Tiuxetan radioimmunotherapy for non-Hodgkin’s lymphoma patients. Bremsstrahlung imaging often faces technical limitations, such as photon scatter and low spatial resolution, which can affect dosimetry precision.
By incorporating machine learning algorithms, particularly Convolutional Neural Networks (CNNs), the team devised a correction method to improve the accuracy of dose estimation. The approach was validated using gold standard Monte Carlo simulations in dosimetry, showing significant potential for improving the clinical precision of radiopharmaceutical therapy.
This achievement reflects not only the intellectual capacity, innovation, and collaborative strength of UGM students but also affirms the ability of Indonesian youth to compete and contribute meaningfully to global advancements in healthcare technology.
Moreover, this accomplishment aligns with the objectives of the Sustainable Development Goals (SDGs). By improving the effectiveness of cancer therapies, the innovation supports SDG 3: Good Health and Well-being, strengthening healthcare services through technology. The cross-disciplinary student collaboration in this scientific research also exemplifies progress in higher education quality, contributing to SDG 4: Quality Education. Furthermore, the application of AI in developing novel dosimetry methods embodies the vision of SDG 9: Industry, Innovation, and Infrastructure, by fostering technological advancement in the health and engineering sectors.
